Fitting parton distribution data with multiplicative normalization uncertainties

doi:10.1007/JHEP05(2010)075

Fitting parton distribution data with multiplicative normalization uncertainties

2010-05-20

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DOI：10.1007/JHEP05(2010)075

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The extraction of robust parton distribution functions with faithful errors requires a careful treatment of the uncertainties in the experimental results. In particular, the data sets used in current analyses each have a different overall multiplicative normalization uncertainty that needs to be properly accounted for in the fitting procedure. Here we consider the generic problem of performing a global fit to many independent data sets each with a different overall multiplicative normalization uncertainty. We show that the methods in common use to treat multiplicative uncertainties lead to systematic biases. We develop a method which is unbiased, based on a self-consistent iterative procedure. We then apply our generic method to the determination of parton distribution functions with the NNPDF methodology, which uses a Monte Carlo method for uncertainty estimation.

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QCD Phenomenology

Fitting parton distribution data with multiplicative normalization uncertainties

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